from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 14.0 | 1.025280 |
| daal4py_KNeighborsClassifier | 0.0 | 3.0 | 21.205253 |
| KNeighborsClassifier_kd_tree | 0.0 | 6.0 | 38.832610 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 43.740270 |
| KMeans_tall | 0.0 | 1.0 | 44.209824 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 17.469926 |
| KMeans_short | 0.0 | 0.0 | 19.505816 |
| daal4py_KMeans_short | 0.0 | 0.0 | 8.757342 |
| LogisticRegression | 0.0 | 1.0 | 2.355693 |
| daal4py_LogisticRegression | 0.0 | 0.0 | 55.327638 |
| Ridge | 0.0 | 0.0 | 0.974624 |
| daal4py_Ridge | 0.0 | 0.0 | 0.645498 |
| total | 0.0 | 31.0 | 14.126336 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.135 | 0.001 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.492 | 0.007 | 0.273 | 0.000 | See |
| 1 | KNeighborsClassifier | predict | 0.174 | 0.012 | 1000000 | 1 | 100 | brute | -1 | 1 | 0.0 | 1.0 | 0.087 | 0.002 | 2.000 | 0.005 | See |
| 2 | KNeighborsClassifier | predict | 25.404 | 0.008 | 1000000 | 1000 | 100 | brute | -1 | 1 | 0.0 | 1.0 | 2.003 | 0.044 | 12.684 | 0.000 | See |
| 3 | KNeighborsClassifier | fit | 0.134 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.489 | 0.005 | 0.275 | 0.001 | See |
| 4 | KNeighborsClassifier | predict | 0.170 | 0.016 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 0.086 | 0.002 | 1.980 | 0.010 | See |
| 5 | KNeighborsClassifier | predict | 36.615 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 1.0 | 1.988 | 0.052 | 18.419 | 0.001 | See |
| 6 | KNeighborsClassifier | fit | 0.122 | 0.001 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.489 | 0.002 | 0.249 | 0.000 | See |
| 7 | KNeighborsClassifier | predict | 0.177 | 0.018 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.085 | 0.001 | 2.079 | 0.010 | See |
| 8 | KNeighborsClassifier | predict | 36.669 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 2.024 | 0.018 | 18.119 | 0.000 | See |
| 9 | KNeighborsClassifier | fit | 0.123 | 0.001 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.490 | 0.004 | 0.250 | 0.000 | See |
| 10 | KNeighborsClassifier | predict | 0.181 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 1 | 0.0 | 1.0 | 0.084 | 0.001 | 2.141 | 0.000 | See |
| 11 | KNeighborsClassifier | predict | 13.474 | 0.046 | 1000000 | 1000 | 100 | brute | 1 | 1 | 0.0 | 1.0 | 1.941 | 0.011 | 6.941 | 0.000 | See |
| 12 | KNeighborsClassifier | fit | 0.123 | 0.001 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.488 | 0.002 | 0.253 | 0.000 | See |
| 13 | KNeighborsClassifier | predict | 0.190 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 0.085 | 0.000 | 2.238 | 0.000 | See |
| 14 | KNeighborsClassifier | predict | 25.727 | 0.104 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 1.0 | 1.951 | 0.015 | 13.185 | 0.000 | See |
| 15 | KNeighborsClassifier | fit | 0.135 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.482 | 0.004 | 0.280 | 0.001 | See |
| 16 | KNeighborsClassifier | predict | 0.189 | 0.002 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.084 | 0.000 | 2.247 | 0.000 | See |
| 17 | KNeighborsClassifier | predict | 25.348 | 0.014 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 2.021 | 0.022 | 12.540 | 0.000 | See |
| 18 | KNeighborsClassifier | fit | 0.060 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.107 | 0.003 | 0.556 | 0.001 | See |
| 19 | KNeighborsClassifier | predict | 0.023 | 0.009 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 0.0 | 0.006 | 0.000 | 3.886 | 0.161 | See |
| 20 | KNeighborsClassifier | predict | 21.676 | 0.056 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 0.0 | 0.303 | 0.004 | 71.500 | 0.000 | See |
| 21 | KNeighborsClassifier | fit | 0.059 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.106 | 0.003 | 0.561 | 0.001 | See |
| 22 | KNeighborsClassifier | predict | 0.033 | 0.004 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 0.0 | 0.006 | 0.001 | 5.421 | 0.040 | See |
| 23 | KNeighborsClassifier | predict | 32.751 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 0.0 | 0.304 | 0.003 | 107.805 | 0.000 | See |
| 24 | KNeighborsClassifier | fit | 0.058 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.106 | 0.001 | 0.547 | 0.000 | See |
| 25 | KNeighborsClassifier | predict | 0.032 | 0.001 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 0.0 | 0.007 | 0.001 | 4.814 | 0.026 | See |
| 26 | KNeighborsClassifier | predict | 32.720 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 0.0 | 0.362 | 0.007 | 90.354 | 0.000 | See |
| 27 | KNeighborsClassifier | fit | 0.061 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.106 | 0.002 | 0.574 | 0.001 | See |
| 28 | KNeighborsClassifier | predict | 0.015 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 0.0 | 0.006 | 0.000 | 2.608 | 0.007 | See |
| 29 | KNeighborsClassifier | predict | 10.435 | 0.014 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 0.0 | 0.303 | 0.003 | 34.459 | 0.000 | See |
| 30 | KNeighborsClassifier | fit | 0.059 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.105 | 0.001 | 0.562 | 0.001 | See |
| 31 | KNeighborsClassifier | predict | 0.027 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 0.0 | 0.006 | 0.001 | 4.355 | 0.055 | See |
| 32 | KNeighborsClassifier | predict | 21.485 | 0.013 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 0.0 | 0.303 | 0.005 | 70.886 | 0.000 | See |
| 33 | KNeighborsClassifier | fit | 0.060 | 0.001 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.106 | 0.004 | 0.566 | 0.002 | See |
| 34 | KNeighborsClassifier | predict | 0.027 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 0.0 | 0.006 | 0.001 | 4.534 | 0.009 | See |
| 35 | KNeighborsClassifier | predict | 21.544 | 0.030 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 0.0 | 0.371 | 0.011 | 58.028 | 0.001 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 3.027 | 0.029 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.727 | 0.018 | 4.165 | 0.001 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.004 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 13.207 | 0.205 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.448 | 0.008 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.104 | 0.003 | 4.327 | 0.001 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 3.032 | 0.034 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 0.744 | 0.010 | 4.074 | 0.000 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 6.459 | 0.240 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.849 | 0.015 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.195 | 0.006 | 4.359 | 0.001 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 3.086 | 0.037 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.759 | 0.018 | 4.066 | 0.001 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.005 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 6.493 | 0.147 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 2.558 | 0.027 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.559 | 0.004 | 4.577 | 0.000 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 3.117 | 0.049 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.766 | 0.014 | 4.069 | 0.001 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 4.491 | 0.264 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.737 | 0.015 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.102 | 0.001 | 7.229 | 0.001 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 3.064 | 0.064 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.740 | 0.014 | 4.141 | 0.001 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 3.220 | 0.236 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.392 | 0.012 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.190 | 0.003 | 7.313 | 0.000 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 3.031 | 0.036 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 0.775 | 0.021 | 3.912 | 0.001 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 3.722 | 0.248 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 4.645 | 0.024 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.559 | 0.003 | 8.310 | 0.000 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.275 | 0.009 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.498 | 0.010 | 2.562 | 0.000 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 24.463 | 0.643 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.028 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 26.619 | 0.045 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.246 | 0.007 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.496 | 0.008 | 2.515 | 0.000 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 13.845 | 0.291 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.033 | 0.003 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 28.250 | 0.074 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.267 | 0.009 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.494 | 0.010 | 2.566 | 0.000 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.001 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 14.183 | 0.466 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.050 | 0.001 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.007 | 0.001 | 6.854 | 0.014 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.268 | 0.009 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.497 | 0.009 | 2.553 | 0.000 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 5.423 | 0.466 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.025 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 24.002 | 0.110 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.262 | 0.010 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.490 | 0.008 | 2.576 | 0.000 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 4.952 | 0.514 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.028 | 0.001 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 24.224 | 0.098 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.266 | 0.009 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.487 | 0.006 | 2.600 | 0.000 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 4.956 | 0.607 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.054 | 0.002 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.007 | 0.001 | 7.576 | 0.028 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.637 | 0.013 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.468 | 0.031 | 1.362 | 0.005 | See |
| 1 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.361 | 0.607 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.602 | 0.332 | See |
| 3 | KMeans_tall | fit | 0.561 | 0.009 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.434 | 0.014 | 1.291 | 0.001 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.287 | 0.531 | See |
| 5 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.048 | 0.546 | See |
| 6 | KMeans_tall | fit | 6.573 | 0.065 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.079 | 0.016 | 2.135 | 0.000 | See |
| 7 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.578 | 0.414 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.824 | 0.198 | See |
| 9 | KMeans_tall | fit | 5.925 | 0.105 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 2.927 | 0.038 | 2.025 | 0.000 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.917 | 0.519 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.066 | 0.184 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.326 | 0.012 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.116 | 0.003 | 2.818 | 0.002 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.021 | 0.506 | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.107 | 0.130 | See |
| 3 | KMeans_short | fit | 0.128 | 0.003 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.047 | 0.001 | 2.729 | 0.002 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.982 | 0.473 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.221 | 0.145 | See |
| 6 | KMeans_short | fit | 0.844 | 0.038 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 19.0 | NaN | 22.0 | NaN | 0.388 | 0.022 | 2.176 | 0.005 | See |
| 7 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.098 | 0.324 | See |
| 8 | KMeans_short | predict | 0.006 | 0.002 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 3.711 | 0.163 | See |
| 9 | KMeans_short | fit | 0.258 | 0.036 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 23.0 | NaN | 20.0 | NaN | 0.183 | 0.026 | 1.408 | 0.039 | See |
| 10 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.894 | 0.286 | See |
| 11 | KMeans_short | predict | 0.004 | 0.003 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 2.825 | 0.579 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 11.382 | 0.014 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 11.396 | 0.031 | 0.999 | 0.000 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.323 | 1.277 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 1.064 | 0.514 | See |
| 3 | LogisticRegression | fit | 0.740 | 0.013 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 0.757 | 0.007 | 0.978 | 0.000 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.000 | 0.133 | 0.407 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.003 | 0.000 | 0.544 | 0.034 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 0.037 | 0.001 | 1000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.021 | 0.003 | 1.782 | 0.021 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 1000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.669 | 0.870 | See |
| 2 | Ridge | predict | 0.000 | 0.000 | 1000 | 100 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.832 | 0.547 | See |
| 3 | Ridge | fit | 0.008 | 0.001 | 10000 | 10000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.005 | 0.002 | 1.722 | 0.156 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 10000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.775 | 0.965 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 10000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.413 | 0.371 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
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"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1",
"setuptools": "49.6.0.post20210108",
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"numpy": "1.20.2",
"scipy": "1.6.2",
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"matplotlib": null,
"joblib": "1.0.1",
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}